ABS is seeking a Data Scientist to join its Artificial Intelligence Practice, supporting a major federal modernization program. The role focuses on applying machine learning, statistical analysis, and modern AI techniques to large datasets in support of mission-critical planning and operations.
Responsibilities
- Analyze large and complex datasets using statistical methods, machine learning, and AI techniques
- Build, test, and maintain predictive models and analytical workflows
- Apply methods including machine learning, deep learning, NLP, generative AI, large language models, and time series analysis to mission-focused data problems
- Support feature engineering, data preparation, model evaluation, and reproducible analytical development
- Assist with transitioning analytics and machine learning capabilities from pilot efforts into production environments
- Contribute to synthetic data development and other advanced analytical methods when appropriate
- Partner with engineers and stakeholders to translate business needs into practical analytical solutions
- Prepare technical documentation, reports, presentations, and other project deliverables
- Support responsible AI practices, including explainability, trustworthiness, and AI risk management
Required Qualifications
- Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related STEM field
- Relevant professional experience applying data science, machine learning, or advanced analytics; depth and scope will vary based on the level filled
- Experience working with large, real-world datasets across the full analytical lifecycle
- Proficiency in Python and working knowledge of SQL
- Experience with machine learning, predictive modeling, model evaluation, and feature engineering
- Familiarity with NLP, GenAI, and LLM methods
- Familiarity with deep learning, neural networks, anomaly detection, and time series methods
- Strong communication skills, including the ability to clearly explain technical findings to varied audiences
- Ability to develop reproducible analytical workflows and clear technical documentation
Preferred Qualifications
- Master’s degree
- Experience supporting production or operational deployment of analytical or machine learning solutions
- Experience in a federal, public sector, or regulated data environment
- Familiarity with survey, demographic, statistical, or population-scale data
- Exposure to record linkage, entity resolution, or matching models
- Experience with synthetic data, differential privacy, or responsible AI practices
Technologies
- Python
- SQL
- NLP
- GenAI
- LLM
- Deep learning
- Neural networks
- Anomaly detection
- Time series analysis
- Large language models
Career Level and Compensation
This position may be filled at multiple career levels based on business need and the selected candidate’s qualifications, relevant experience, and demonstrated capability. Typical leveling is as follows: Junior (0 to 4 years), Mid-Level (5 to 9 years), Senior (10 to 14 years), Principal (15 or more years). These ranges are guidelines only and are not the sole determining factor in level.
The posted compensation range reflects the full range across all possible levels. Individual offers will be based on the level at which the candidate is hired and factors such as skills, experience, internal equity, and geographic market considerations where applicable.
Reporting Relationships
Reports directly to the Chief Data Scientist or a Manager, Director, or Executive role.
Location and Work Arrangement
Based in the Washington, D.C. metro area, with primary work performed in Suitland, Maryland. Remote or hybrid arrangements may be available for eligible work, subject to government approval.
